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混合分布估计算法求解随机Job shop提前/拖期调度问题
分布估计算法 提前/拖期
2016/1/5
针对加工时间具有随机特性的Job shop 调度问题, 提出基于分布估计算法的混合算法. 为增强分布估计算法的种群多样性, 定义了父代工序继承率并设计一种可保留父代个体优良结构特征的重组方法, 该方法在继承父代个体优良结构特征的同时避免了非法解的产生. 在个体选择评价阶段, 采用最优计算量分配策略为每个个体分配模拟量以提高个体评价的精确性. 仿真算例表明了所提出算法的有效性和鲁棒性.
HIGH GROWTH JOB TRAINING INITIATIVE FOR REMOTE SENSING COMMUNITY
Job Training Web-based e-Learning
2015/8/24
An innovative geospatial training and awareness program has been initiated by a consortium led by Geospatial21 and the
International Center for Remote Sensing Education, to include an apprenticeship...
Modified NSGA-II for a Bi-Objective Job Sequencing Problem
Job Sequencing Multi-Objective Evolutionary Algorithm (MOEA) NSGA-II (Non-Dominated Sorting Genetic Algorithm-II) Tardiness Deterioration Cost
2013/1/28
This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contai...
Preventive maintenance optimization for a multi-component system under changing job shop schedule
Multi-component Preventive maintenance Job shop schedule Dynamic Cost Optimization
2012/4/16
Variability and small lot size is a common feature for many discrete manufacturing processes designed to meet a wide array of customer needs. Because of this, job shop schedule often has to be continu...
New recruit safety expectations: Relationships with trust and perceived job risk
Trust Expectations New recruits Psychological contract
2012/4/14
Very little research has examined the safety expectations of new recruits, particularly those of individuals about to enter full-time work for the first time. There is evidence that new recruits have ...
New Hybrid Parallel Algorithm for Variable-sized Batch Splitting Scheduling with Alternative Machines in Job Shops
variable-sized batch splitting differential evolution alternative machines
2011/8/3
The batch splitting scheduling problem has recently become a major target in manufacturing systems, and the researchers have obtained great achievements, whereas most of existing related researches fo...
求解多目标job-shop生产调度问题的量子进化算法
多目标作业车间调度 量子进化算法 局域搜索
2010/8/30
基于量子计算理论和进化理论，提出了用于多目标job-shop优化的量子进化算法（QEA-MOJSP）。QEA-MOJSP采用量子比特来表示工序对加工顺序的优先概率，利用量子叠加和相干机理，通过更新和交叉操作完成进化过程。对所有机器上工序对优先概率进行观测可得到一个调度方案，修补算子被用于不可行调度方案的修补。设计了局部搜索算子用于开采当代最优个体周围的解空间，以提高算法的收敛速度。实验结果表明，对...
The relationship between information technology adoption and job satisfaction in contracting companies in Jordan
Construction industry contracting companies IT adoption job satisfaction Jordan
2010/9/29
Despite the popularity of Information Technology and job satisfaction research, little empirical evidence (to the researcher's knowledge) exists of the relationship between IT adoption and job satisfa...
A Content Analysis of Australian IS Early Career Job Advertisements
Content Analysis Australian Career Job Advertisements
2009/12/9
The purpose of this paper is to develop an understanding of the knowledge, skills and competencies demanded of early career information systems graduates in Australia. Job advertisements from 2006 wer...
改进混合量子算法在Job Shop调度中的研究
混合量子算法 优化 调度
2009/11/19
自从科学的管理思想引进生产过程中，管理者开始注重计算机的辅助作用。Job Shop调度问题（JSP）是许多实际生产调度的简化模型，由于解空间的规模巨大，给求解带来了很大的挑战。在量子比特编码的基础上，设计了两种解码方式，结合微粒群算法（PSO）的更新式对量子角进行智能调整，形成了混合量子算法（HQA）。但HQA在求解JSP时，效果并不好。在HQA的框架下，增加了一些寻优机制，使得算法求解性能有显著...
激素调节机制IAGA在作业车间调度中的应用（Job-shop Scheduling Problem Based on Improved Adaptive Genetic Algorithm with Hormone Modulation Mechanism）
作业车间调度 激素调节机制 改进型自适应遗传算法
2009/11/3
针对离散型生产作业中的车间调度问题，以最大流程时间最小化为目标，将基于激素调节机制的改进型自适应遗传算法应用其中。该算法具有有效避免近亲繁殖、无需复制操作、有效克服早熟现象和进化缓慢问题等特点。算法采用基于工序的编码方式，并在调度实例应用中取得满意效果。仿真结果表明：该算法大幅度减少了调度方案生成时间，优化了调度方案，缩减了最小化完工时间，能够有效、高质量地解决作业车间调度问题。
A Combined Analytical Method of Job Evaluation
Job Evaluation Point Rating Factor Comparison Factor Plan Linear Programming
2009/10/14
This study includes the design and application of a job evaluation scheme in a metal working company.The first step was the design of a system for determining the weights of job factors from sets of p...
用带变异因子的QPSO算法解决Job-Shop调度问题
遗传算法 粒子群优化算法 量子粒子群优化算法
2009/7/6
由于量子粒子群优化算法仍有可能会出现早熟现象，因此将变异机制引入量子粒子群优化算法以使算法跳出局部最优并增强其全局搜索能力，并将改进后的量子粒子群优化算法用于求解作业车间调度问题。仿真实例表明，该算法具有良好的全局收敛性能和快捷的收敛速度，调度效果优于遗传算法、粒子群优化算法和量子粒子群优化算法。
动态评价免疫微粒群算法在Job-shop调度中的应用
微粒群优化 免疫 作业车间调度
2009/6/16
传统粒子群优化算法在解决组合优化问题上具有一定的局限性，通过分析其优化机理，对迭代公式加以改进，提出了改进微粒群算法。算法中，利用遗传算法的交叉思想来完成粒子间的信息交换，以期达到粒子更新。粒子进化过程中，为保留群体中的优秀粒子，使用了加速度这一优化算子。为避免粒子陷入局部搜索，迭代过程中使用免疫算法来动态评价微粒群体。通过大量实验仿真，算法可以有效求解作业车间调度问题，验证了算法的合理性。
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基于遗传算法的Job-Shop调度问题求解
遗传算法 Job-Shop调度问题 模型
2009/3/6
针对 JobShop调度问题，详细讨论了遗传算法以及染色体编码方法，建立了算法模型。通过仿真实验，验证了该算法的有效性。